{"id":"W2074708241","doi":"10.1657/1938-4246(intro)[beylich]2.0.co;2","title":"Sediment Budgets In Cold Environments—The Sedibud Program. Introduction","year":2009,"lang":"en","type":"article","venue":"Arctic Antarctic and Alpine Research","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Snow; Precipitation; Environmental science; Sediment; Climate change; Hydrology (agriculture); Cold climate; Physical geography; Climatology; Geology; Geography; Meteorology; Oceanography; Geomorphology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000915077,0.0005296607,0.0003087004,0.001541019,0.0004571444,0.0009584122,0.0007626844,0.0002572178,0.002921273],"category_scores_gemma":[0.0007380543,0.0001630649,0.0003017123,0.002632244,0.0002108443,0.0005150901,0.0009204039,0.0002624985,0.0004594999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002412833,"about_ca_system_score_gemma":0.00200684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2512895,"about_ca_topic_score_gemma":0.3477296,"domain_scores_codex":[0.9998461,0.00002924858,0.000008544467,0.00003363397,0.00005641899,0.00002601398],"domain_scores_gemma":[0.9995894,0.00004103929,0.00009394561,0.00003392405,0.0001425368,0.00009925881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001175058,0.0003498583,0.6502693,0.0003843131,0.0004237765,0.0001594723,0.0003694652,0.04387419,0.002492769,0.004788246,0.07613322,0.2195803],"study_design_scores_gemma":[0.0002275594,0.0001986795,0.7920961,0.0001601051,0.0001584019,0.00004343566,0.000370646,0.01444747,0.003443912,0.002771385,0.1860456,0.00003676716],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7003188,0.006609262,0.002615236,0.005572814,0.0001950552,0.0001792835,0.2342542,0.0008874498,0.04936788],"genre_scores_gemma":[0.8885394,0.003629021,0.006901204,0.0004370683,0.0001685837,0.0002575073,0.07868776,0.0002244907,0.02115496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2512895,"threshold_uncertainty_score":0.4996536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04709083714538511,"score_gpt":0.3132278603838621,"score_spread":0.266137023238477,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}